What You Need to Know About Key Industries: Data Science and the Job Search

What You Need to Know About Key Industries: Data Science and the Job Search
Data science is a relatively new industry, although the core concepts behind it (statistics, data analysis and business analysis) have existed for decades. After being dubbed "The Sexist Job of the 21st Century" by Forbes, everyone from corporations to college students has been eager to get on the big data bandwagon. But if you really want to work in the industry, there are a couple of things that you need to understand about the job search process.
Job Description Over Job Title
Take a look at any job board and you'll see that there is no shortage of listing for Data Scientists. However, since most companies are still in the nascent stage of building of their data science department, job descriptions for Data Scientists often vary significantly from one business to the next. If a job listing mentions tools like Excel, Google Analytics or Tableau and little or nothing about programming languages like Python, R or SQL, these companies are looking for a Data or Marketing Analyst and not a Data Scientist. Conversely, if a job says Data Analyst but requires knowledge of the data science stack (pandas, numpy, scipy etc.), algorithms or natural language processing (NLP), this is really a data scientist position and the compensation should reflect the complexities of the job.
Expectations vs. Reality
Due to the multidisciplinary nature of data science, and the strong desire many companies have to quickly get into the industry, expectations rarely meet with reality. As a result, you will see many job descriptions requiring a PhD, advanced machine learning knowledge, experience deploying production ready algorithms, and five years of full-time work experience in the industry. This is often referred to by job seekers as a "purple squirrel", or someone with a mythical array of skills which few possess. Solid programming skills, a master's degree in a quantitative field and some hands-on experience with machine learning, demonstrated with projects or Kaggle competition participation, are often enough to get you to the interview stage.
As data becomes an increasing integral in our lives, the need to process and make sense of this data is sure to continue to grow. Now that you know what it really takes to work in the field, you are that much closer to realizing your dream of being a Data Scientist. Please contact us to learn about relevant career options.